Urban Air Quality Matrix: Spatiotemporal Heterogeneity and Source Diagnostics in Bengaluru

Rapid urbanisation in tropical megacities has engendered complex atmospheric regimes characterised by extreme spatiotemporal heterogeneity. This study presents a comprehensive statistical characterisation of the ambient air quality matrix in Bengaluru, India (2018–2024), leveraging a high-density network of 13 Continuous Ambient Air Quality Monitoring Stations (CAAQMS). Moving beyond aggregate compliance metrics, this study employs an integrated statistical framework using the Mann-Kendall trend test, Coefficient of Divergence (COD), and Multi-Dimensional Scaling (MDS). Results indicate a 'fractured airshed' (defined as a domain exhibiting high spatial heterogeneity, COD > 0.20): the industrial node (Peenya) recorded a statistically significant decline in PM2.5 (Sen’s Slope: −2.75 μg/m³/year), contrasting with a statistically significant increased trend of Ammonia (NH₃) in residential zones (+1.44 μg/m³/year). Spatial analysis revealed a high Coefficient of Divergence (COD = 0.42) between industrial and residential zones, refuting the hypothesis of a homogenous urban airshed. Further, source diagnostics quantified a weekend effect with an 18.4% reduction in NO₂ (p < 0.01), isolating the vehicular contribution to the pollution burden. These findings underscore the critical need for a Zonal Air Quality Management (ZAQM) framework.